Ignite Creation Date:
2024-05-06 @ 6:50 PM
Last Modification Date:
2024-10-26 @ 2:56 PM
Study NCT ID:
NCT05809232
Status:
NOT_YET_RECRUITING
Last Update Posted:
2023-04-12
First Post:
2023-03-14
Brief Title:
Impact of Machine Learning-based Clinician Decision Support Algorithms in Perioperative Care
Sponsor:
Singapore General Hospital
Organization:
Singapore General Hospital
Study Overview
Official Title:
Impact of Machine Learning-based Clinician Decision Support Algorithms in Perioperative Care - A Randomized Control Trial IMAGINATIVE Trial
Status:
NOT_YET_RECRUITING
Status Verified Date:
2023-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
IMAGINATIVE
Brief Summary:
Predicting surgical risks are important to patients and clinicians for shared decision making process and management plan The study team aim to conduct a hybrid type 1 effectiveness implementation study design A Randomized Controlled Trial where participants undergoing surgery In Singapore General Hospital SGH will be allocated in 11 ratio to CARES-guided unblinded to risk level or to unguided blinded to risk level groups All participants undergoing elective surgeries in SGH will be considered eligible for enrolment into the study For elective surgeries the participants will mainly be recruited from Pre-admission Centre The outcome of this study will help patients and clinicians make better decisions together Firstly the deployment of the CARES model in a live clinical environment could potentially reduce postoperative complications and improve the quality of surgical care provision The findings from this study would allow fine-tuning of CARES as well as further deployment of additional risk models for specific complications other than Mortality and ICU stay This in turn would translate to better health for the surgical population and improved cost-effectiveness This is significant as the surgical population is expected to continuously grow due to improved access to care better technologies and the aging population Secondly IMAGINATIVE will be instrumental in improving our understanding of the deployment strategies for AIML predictive models in healthcare Models such as CARES could be the standard of care in the future if proven to improve the health outcomes of patients As model deployments are costly and can be disruptive to the EMR processes this study would be the initial spark for future deployment and health services research focusing on improving the value of these model deployments
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None